Instructions to use murat/kyrgyz_language_NER with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use murat/kyrgyz_language_NER with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="murat/kyrgyz_language_NER")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("murat/kyrgyz_language_NER") model = AutoModelForTokenClassification.from_pretrained("murat/kyrgyz_language_NER", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from murat/kyrgyz_language_NER: direct link, hf CLI and curl.
- Browser
- Download file 709 MB
-
https://huggingface.co/murat/kyrgyz_language_NER/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://murat/kyrgyz_language_NER/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/murat/kyrgyz_language_NER/resolve/main/pytorch_model.bin
709 MB
- Xet hash:
- 3401887b1007fd7221c6b044a044072a1cf0ecc67e4c073cb86ddf526ae5ce58
- Size of remote file:
- 709 MB
- SHA256:
- 7f1ab730f4d94b20d18d99089d05b3f2e3c07cc07c8153ee6a9bb92538e9902c
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